The goal of this project is to characterize two sources of extrinsic variability that are present in gene regulatory networks. Transcription and regulation are constantly being affected by extrinsic sources of variability, and it is an open question how gene networks reliably function under these conditions. The first specific aim of this proposal addresses the variability caused by cell cycle dynamics in different types of gene regulatory networks. As a cell grows and divides, the changes in the volume of the cell cause variability in the concentrations of the reactants that are active in the regulatory pathways. Since the rates of the underlying biochemical reactions depend on the concentrations of the reactants, the dynamics of gene networks will be affected by the cell cycle. The second specific aim of this proposal is the examination of the cell-to-cell variability in gene networks when their transcription is induced by an outside agent. Many gene networks can be turned on by introducing a chemical inducer into the growth media. Often, these networks up-regulate the transport protein responsible for the internalization of the inducer once it has been introduced. This positive feedback can create high cell-to-cell variability in the time between introduction of the inducer and the time at which the network is completely active. These aims will be addressed using a multidisciplinary approach involving both experimental and computational methods. The experimental aspects will be threefold. First, standard molecular biology techniques will be used to create the needed gene networks and to add fluorescent reporter proteins. Second, existing microfludic devices, developed in this lab, will be used to both control the growth conditions of cells and record cell data with the use of fluorescent microscopy. Finally, the fluorescent images obtained from the microscopy will be analyzed with existing cell tracking software to obtain trajectories of individual cells. The computational modeling will entail discrete stochastic simulations of comprehensive models of the networks involved, and will be used to both describe and predict the behavior of the experiments. The results of experiments will then be used, in turn, to generate more complete models and a more coherent understanding of the networks involved. One of the main goals of systems biology is to understand the dynamics of gene regulatory networks. One obstacle to this goal is the characterization of extrinsic variability, and the understanding of how gene networks reliably function in noisy environments. The specific aims of this proposal will address these fundamental aspects of transcriptional regulation. [unreadable] [unreadable] [unreadable]